Image Compression Using Adaptive Wavelets and Trellis-Coded Quantization

  • Ioannis Katsavounidis
  • C.-C. Jay Kuo
  • Z. Zhang
Conference paper


In this work we present some new results on still image compression. The first step involves adaptive transform (AWT) as the fundamental means of de-correlation of the image pixel values. The wavelet decomposition scheme is an adaptive one, where at each point a locally optimal decision is taken regarding whether a wavelet decomposition step is to be applied and also the direction of the filter, (along image lines or columns) and the choice of wavelet filter, using the optimal bit allocation formula. The same formula also determines the scanning oder and the bit rate allocated for each resulting wavelet subband. The next step is the application of multistage Trellis-Coded Quantization (MTCQ) on the various subband. To do so, we use a family of MTCQ quantizers, parametized by the target bit rate. Progressive transmission is achieved by quantization of the residual error.


Wavelet Coefficient Filter Design Wavelet Filter Analysis Filter Synthesis Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag 1999

Authors and Affiliations

  • Ioannis Katsavounidis
    • 1
  • C.-C. Jay Kuo
    • 1
  • Z. Zhang
    • 1
  1. 1.Department of Electrical Engineering-SystemsUniversity of Southern CaliforniaLos AngelesUnited States

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